SAS Support Communities

Mystik · ‎03-19-2020

Thank you Reeza! Actually, it was your solution that actually works. Dunno why i marked mine as the solution. Thanks again.

Mystik · ‎03-19-2020

Thank you. I did as Reeza says and it worked.

Mystik · ‎03-18-2020

I replaced "PROC SURVEYSELECT" statement with SELECTALL as you suggested (find below) but got the error message: 6 selectall data=m4_case&i method=srs n=10 seed=2009 out=m6_case&i; --------- 180 ERROR 180-322: Statement is not valid or it is used out of proper order. selectall data=m4_case&i method=srs n=10 seed=2009 out=m6_case&i; id IDnum case_id ctrl_id dx grp_cc; run;

Mystik · ‎03-18-2020

Hello, I am running a nested case-control sampling macro analysis matching on n=10 controls. i.e.. proc surveyselect data=m4_case&i method=srs n=10 seed=2009 out=m6_case&i; id IDnum case_id ctrl_id dx grp_cc; run; However, i get these messages when the matching number is less than 10; ERROR: The sample size, 10, is greater than the number of sampling units, 9. NOTE: The SAS System stopped processing this step because of errors. WARNING: The data set M6_CASE2096 may be incomplete. When this step was stopped there were 0 observations and 5 variables. I have relaxed my matching criteria to accommodate more case-control matches as possible. For now i want to force the sas program to accept those n=9 etc to be matched using the same procedure stated above whilst still using the n=10 criteria. Pls any help will be welcome.

Mystik · ‎12-09-2019

Yes i agreed univariate is one variable in the model but remember there is sex in there bcos i wanted to stratify by sex (male vs female) to create a table stratified by sex. As i said earlier, the dependent variable is sex and In this case you have to include sex. Eventually, i got it all figured out as the problem was coming from the "estimate" side; e.g. -1 1 and -1 1 0 0 for males. So the sas code below worked perfectly for me now. proc genmod data=avia88 desc; class sex csa; model acet=sex csa sex*csa/link=logit dist=binomial type3; estimate "M:" csa -1 1 csa*sex -1 1 0 0/exp; estimate "W:" csa -1 1 csa*sex 0 0 -1 1/exp; run;

Mystik · ‎12-08-2019

Thank you. here is it. proc genmod data=avia88 desc; class sex; model acet=sex csa sex*csa/link=logit dist=binomial type3; estimate "M:" sex csa csa*sex 1 -1 0 0/exp; estimate "W:" sex csa csa*sex 0 0 -1 1/exp; run; the independent variable is sex. adjusting for csa (1,0), age(18, 23, 89 etc) etc... but for now i want to do a univariable analyses with each variable one by one in the form of OR 95CI

Mystik · ‎12-08-2019

made a mistake in the first one. This is it below: proc genmod data=avia88 desc; class sex; model acet=sex csa sex*csa/link=logit dist=binomial type3; estimate "M:" csa csa*sex 1 -1 0 0/exp; estimate "W:" csa csa*sex 0 0 -1 1/exp; run

Mystik · ‎12-08-2019

Hello, so am running a univariate analyses by putting each variable alone in the model. the outcome is acet; the dependent variable is sex (coded Men=1 and Women=2) the independent variables are; csa (coded as 1 or 0) and age (coded which is numeric i.e. 18, 32, 56, 89, etc) For example below; i tried putting only sex in the model but i keep getting error from the SAS log. please any help? proc genmod data=avia88 desc; class sex; model acet=csa sex*csa/link=logit dist=binomial type3; estimate "M:" csa csa*sex 1 -1 0 0/exp; estimate "W:" oral_cs csa*sex 0 0 -1 1/exp; run;

Mystik · ‎11-27-2019

WORKED!!! THANKS

Mystik · ‎11-27-2019

i have over 30,000 subjects with over 120, 000 observations and 15 variables. Pls your first data step with the datalines wouldn't work. I gave the above dataline just to give a brief description of the data. if you kindly give me another data steps to run the first step. thank you.

Mystik · ‎11-27-2019

sorry this is a data with over 120,000 observations and 16 variables. the expected out put is to work with subjects (such as T02 and T03) that do not have duplicates. This stage is the exclusion stage before the incoming logistic analyses.

Mystik · ‎11-27-2019

Thanks. Actually there are no missing values; for instance this is how the data looks like; ID indexdate Grp 1 Grp2 hxdate hx_60 T01 11Jun2006 OCS OCS 11Jun2006 1 T01 11Jun2006 OCS ** 21Jul2006 1 **=MISSING T01 11Jun2006 OCS OCS 16Sep2006 1 T02 06Jan2010 BASA BASA 06Jan2010 1 T03 12May2013 LOMA LOMA 12May2013 1 T04 17Sep2007 ABAS ABAS 17Sep2007 1 T04 17Sep2007 ABAS ** 19Oct2007 1 T04 17Sep2007 ABAS ** . 11Dec2007 1 As depicted above, Subject with ID=T01 has 3 duplicates and needs to be excluded, i.e delete T01 and not the duplicates. Also T04

Mystik · ‎11-27-2019

Hello, Pls can someone help me to delete subjects that have duplicates; not the duplicates but any subject that has duplicates recordings (variable is hx_60), that subject must be deleted. The prog below does not work for me but only deletes duplicates but not the subject having duplicates; proc sort data=krag.px_60 out=krag.px_60a noduprecs; by subject_ID hx_60; run;

Mystik · ‎11-29-2018

Thank you. however, i will still get duplicates because, those codes in medic variable which are not 1, 2, 3 will still be available in medic variable. So those observations will still be present in medic. Running a proc freq on outcome variable will yield those values not coded 1,2 or 3 as missing. Also the outcome variables of 1, 2 or 3 are based on a single code in medic or combination of codes.

Mystik · ‎11-29-2018

Hello. I have a SAS file called Prg_grp. One of the variables in this file is called "outcomes" coded as 0,1,2 or 3. 1 in the outcome denotes = asthin 2 = Coap 3 = Soca However any of my outcome that is not either of the above is denoted = 0. I have 11, 829,526 of observations but my total number based on ID without duplications is 85,000. My file has other variables such as ID, medic, medic_date. I want to remove duplicates so that only an ID has either 1, 2, or 3 and the total number of rows corresponding to my ID is exactly 85,000.

Online Status	Offline
Date Last Visited	‎03-20-2020 06:58 PM

SAS Support Communities

Re: nested case-control sampling macro analysis matching

Re: nested case-control sampling macro analysis matching

Re: nested case-control sampling macro analysis matching

nested case-control sampling macro analysis matching

Re: How do i run a univariate analysis for this?

Re: How do i run a univariate analysis for this?

Re: How do i run a univariate analysis for this?

How do i run a univariate analysis for this?

Re: Delete subjects that have duplicates; not the duplicates

Re: Delete subjects that have duplicates; not the duplicates

Re: nested case-control sampling macro analysis matching

Re: Full Join using proc sql

Re: Full Join using proc sql

Re: nested case-control sampling macro analysis matching

Re: Full Join using proc sql

Re: nested case-control sampling macro analysis matching

Re: nested case-control sampling macro analysis matching

Re: nested case-control sampling macro analysis matching

nested case-control sampling macro analysis matching

Re: How do i run a univariate analysis for this?

Re: How do i run a univariate analysis for this?

Re: How do i run a univariate analysis for this?

How do i run a univariate analysis for this?

Re: Delete subjects that have duplicates; not the duplicates

Re: Delete subjects that have duplicates; not the duplicates

Re: Delete subjects that have duplicates; not the duplicates

Re: Delete subjects that have duplicates; not the duplicates

Delete subjects that have duplicates; not the duplicates

Re: How do i remove duplicates from my outcomes?

How do i remove duplicates from my outcomes?

Follow Us

What is...